A model-agnostic API exposes application behavior through a stable interface while allowing the underlying model or orchestration layer to change.
The boundary
Clients depend on request and response behavior, not provider internals.
Why it matters
Models, prompts, retrieval systems, and providers can change quickly; stable contracts reduce migration cost.
Portfolio evidence
The documented chatbot decouples its LangChain pipeline from the Flask API to support backend replacement.
Failure condition
A replacement backend must satisfy the same contract and pass the same quality and reliability tests.
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Related work and reading
LLM Applications
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Flask + LLM Service Contract
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LLM Conversational Chatbot
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AI Developer / ML Engineer building end-to-end AI systems from research to production, with a focus on multimodal AI, LLM applications, retrieval, MLOps, and systems engineering. He is based in Rawalpindi, Pakistan and is the founder of GROVE SYSTEMS.